private void btnNetworkNew_Click(object sender, EventArgs e)
{
string numInputs = this.txtNumInput.Text;
string numHiddens = this.txtNumHidden.Text;
string numOutputs = this.txtNumOutput.Text;
if (numInputs == "" || numHiddens == "" || numOutputs == "")
{
System.Windows.Forms.MessageBox.Show("Please insert the number of Input Nodes, Hidden Nodes, Output Nodes", null, System.Windows.Forms.MessageBoxButtons.OK);
return;
}
try
{
NeuralModel = new Neural(Int32.Parse(numInputs), Int32.Parse(numHiddens), Int32.Parse(numOutputs));
NeuralModel.SetData(_errorSeries);
System.Windows.Forms.MessageBox.Show("NetWork configuration successfull, You can train it");
this.txtNumOutput.Enabled = false;
this.txtNumHidden.Enabled = false;
this.txtNumInput.Enabled = false;
this.btnNetworkNew.Enabled = false;
this.btnNetworkLoad.Enabled = false;
this.btnNetworkSave.Enabled = true;
this.btnNetworkClear.Enabled = true;
this.btnTrainNeural.Enabled = true;
}
catch (Exception exception)
{
System.Windows.Forms.MessageBox.Show(exception.Message);
}
}
private void InitData()
{
_dataSeries = new List <double>();
_errorSeries = new List <double>();
ARIMAModel = new ARIMA();
NeuralModel = new Neural();
}
private void button1_Click(object sender, EventArgs e)
{
_errorSeries = _dataSeries.FindAll(item => true);
NeuralModel = new Neural();
NeuralModel.SetData(_errorSeries);
btnNetworkNew.Enabled = true;
btnNetworkLoad.Enabled = true;
btnPlotNeural.Enabled = true;
this.txtNumOutput.Enabled = false;
this.txtNumHidden.Enabled = true;
this.txtNumInput.Enabled = true;
}
private void btnNetworkClear_Click(object sender, EventArgs e)
{
NeuralModel = new Neural();
NeuralModel.SetData(_errorSeries);
this.txtNumInput.Text = "";
this.txtNumHidden.Text = "";
this.txtNumInput.Enabled = true;
this.txtNumHidden.Enabled = true;
this.btnNetworkNew.Enabled = true;
this.btnNetworkLoad.Enabled = true;
this.btnNetworkSave.Enabled = false;
this.btnNetworkClear.Enabled = false;
this.btnTrainNeural.Enabled = false;
this.btnTestNeural.Enabled = false;
this.btnForecastNeural.Enabled = false;
}
private void btnNetworkSave_Click(object sender, EventArgs e)
{
SaveFileDialog saveDialog = new SaveFileDialog();
saveDialog.Title = "Save Network Config File";
saveDialog.DefaultExt = "xml";
DialogResult result = saveDialog.ShowDialog();
string dataFile = "";
if (result == System.Windows.Forms.DialogResult.OK)
{
dataFile = saveDialog.FileName;
bool exportResult = Neural.Export(NeuralModel, dataFile);
}
else
{
return;
}
}
private void btnNetworkLoad_Click(object sender, EventArgs e)
{
OpenFileDialog fileDialog = new OpenFileDialog();
fileDialog.Title = "Load Network Config File";
fileDialog.DefaultExt = "xml";
DialogResult result = fileDialog.ShowDialog();
string dataFile = "";
if (result == System.Windows.Forms.DialogResult.OK)
{
dataFile = fileDialog.FileName;
Neural temp = Neural.Import(dataFile);
if (temp == null)
{
System.Windows.Forms.MessageBox.Show("The Input file is not correct format !!!", null, System.Windows.Forms.MessageBoxButtons.OK);
}
else
{
NeuralModel = temp;
NeuralModel.SetData(_errorSeries);
this.txtNumInput.Text = NeuralModel.m_iNumInputNodes.ToString();
this.txtNumHidden.Text = NeuralModel.m_iNumHiddenNodes.ToString();
this.btnNetworkNew.Enabled = false;
this.btnNetworkLoad.Enabled = false;
this.btnNetworkSave.Enabled = true;
this.btnNetworkClear.Enabled = true;
this.btnTrainNeural.Enabled = true;
this.btnForecastNeural.Enabled = true;
this.btnTestNeural.Enabled = true;
this.btnForecast.Enabled = true;
this.btnTest.Enabled = true;
}
}
else
{
return;
}
}
public static bool Export(Neural network, string pathFile)
{
XmlDocument doc = new XmlDocument();
XmlElement root = doc.CreateElement("Network");
doc.AppendChild(root);
//save number of Input, Hidden, Output Nodes
XmlElement numInput = doc.CreateElement("numInputNodes");
numInput.InnerText = Convert.ToString(network.m_iNumInputNodes);
XmlElement numHidden = doc.CreateElement("numHiddenNodes");
numHidden.InnerText = Convert.ToString(network.m_iNumHiddenNodes);
XmlElement numOutput = doc.CreateElement("numOutputNodes");
numOutput.InnerText = Convert.ToString(network.m_iNumOutputNodes);
root.AppendChild(numInput);
root.AppendChild(numHidden);
root.AppendChild(numOutput);
//save input nodes
XmlElement InputNodes = doc.CreateElement("InputNodes");
for (int i = 0; i <= network.m_iNumInputNodes; i++)
{
XmlElement aInputNode = doc.CreateElement("Input" + Convert.ToString(i + 1));
//save activation func
if (network.m_arInputNodes[i].m_activeFuncType == ActionvationFunction.SIGMOID_FUNCTION)
{
XmlElement actFunc = doc.CreateElement("activateFunc");
actFunc.InnerText = "SIGMOID_FUNCTION";
aInputNode.AppendChild(actFunc);
}
//save weight for in-hid connection
for (int j = 0; j < network.m_iNumHiddenNodes; j++)
{
XmlElement aWeight = doc.CreateElement("InHid" + Convert.ToString(i + 1) + Convert.ToString(j + 1));
aWeight.InnerText = Convert.ToString(network.m_arInputHiddenConn[i, j]);
aInputNode.AppendChild(aWeight);
}
InputNodes.AppendChild(aInputNode);
}
root.AppendChild(InputNodes);
//save hidden nodes
XmlElement HiddenNodes = doc.CreateElement("HiddenNodes");
for (int i = 0; i <= network.m_iNumHiddenNodes; i++)
{
XmlElement aHiddenNode = doc.CreateElement("Hidden" + Convert.ToString(i + 1));
//save activation func
if (network.m_arHiddenNodes[i].m_activeFuncType == ActionvationFunction.SIGMOID_FUNCTION)
{
XmlElement actFunc = doc.CreateElement("activateFunc");
actFunc.InnerText = "SIGMOID_FUNCTION";
aHiddenNode.AppendChild(actFunc);
}
//save weight for hid-out connection
for (int j = 0; j < network.m_iNumOutputNodes; j++)
{
XmlElement aWeight = doc.CreateElement("HidOut" + Convert.ToString(i + 1) + Convert.ToString(j + 1));
aWeight.InnerText = Convert.ToString(network.m_arHiddenOutputConn[i, j]);
aHiddenNode.AppendChild(aWeight);
}
HiddenNodes.AppendChild(aHiddenNode);
}
root.AppendChild(HiddenNodes);
//save output nodes
XmlElement OutputNodes = doc.CreateElement("OutputNodes");
for (int i = 0; i < network.m_iNumOutputNodes; i++)
{
XmlElement aOutputNode = doc.CreateElement("Output" + Convert.ToString(i + 1));
//save activation func
if (network.m_arOutputNodes[i].m_activeFuncType == ActionvationFunction.SIGMOID_FUNCTION)
{
XmlElement actFunc = doc.CreateElement("activateFunc");
actFunc.InnerText = "SIGMOID_FUNCTION";
aOutputNode.AppendChild(actFunc);
}
OutputNodes.AppendChild(aOutputNode);
}
root.AppendChild(OutputNodes);
doc.Save(pathFile);
return(true);
}
public static Neural Import(string pathFile)
{
XmlDocument input = new XmlDocument();
Neural loadedNetwork = null;
try
{
input.Load(pathFile);
XmlNode root = input.FirstChild;
//Get number of input, hidden, output nodes
int numInputNodes = Int32.Parse(root.SelectSingleNode("descendant::numInputNodes").InnerText);
int numHiddenNodes = Int32.Parse(root.SelectSingleNode("descendant::numHiddenNodes").InnerText);
int numOutputNodes = Int32.Parse(root.SelectSingleNode("descendant::numOutputNodes").InnerText);
//create a network
loadedNetwork = new Neural(numInputNodes, numHiddenNodes, numOutputNodes);
//Get Input Nodes
for (int i = 0; i <= loadedNetwork.m_iNumInputNodes; i++)
{
//get a input node
XmlNode tempNode = root.SelectSingleNode("descendant::Input" + Convert.ToString(i + 1));
//get activation function type
string activationFunc = tempNode.SelectSingleNode("descendant::activateFunc").InnerText;
if (activationFunc.Equals("SIGMOID_FUNCTION"))
{
loadedNetwork.m_arInputNodes[i].m_activeFuncType = ActionvationFunction.SIGMOID_FUNCTION;
}
//get weight
for (int j = 0; j < loadedNetwork.m_iNumHiddenNodes; j++)
{
loadedNetwork.m_arInputHiddenConn[i, j] = Convert.ToDouble(tempNode.SelectSingleNode("descendant::InHid" + Convert.ToString(i + 1) + Convert.ToString(j + 1)).InnerText);
}
}
//Get Hidden Nodes
for (int i = 0; i <= loadedNetwork.m_iNumHiddenNodes; i++)
{
//get a hidden node
XmlNode tempNode = root.SelectSingleNode("descendant::Hidden" + Convert.ToString(i + 1));
//get activation function type
string activationFunc = tempNode.SelectSingleNode("descendant::activateFunc").InnerText;
if (activationFunc.Equals("SIGMOID_FUNCTION"))
{
loadedNetwork.m_arHiddenNodes[i].m_activeFuncType = ActionvationFunction.SIGMOID_FUNCTION;
}
for (int j = 0; j < loadedNetwork.m_iNumOutputNodes; j++)
{
loadedNetwork.m_arHiddenOutputConn[i, j] = Convert.ToDouble(tempNode.SelectSingleNode("descendant::HidOut" + Convert.ToString(i + 1) + Convert.ToString(j + 1)).InnerText);
}
}
//Get Output Nodes
for (int i = 0; i < loadedNetwork.m_iNumOutputNodes; i++)
{
//get a output node
XmlNode tempNode = root.SelectSingleNode("descendant::Output" + Convert.ToString(i + 1));
//get activation function type
string activationFunc = tempNode.SelectSingleNode("descendant::activateFunc").InnerText;
if (activationFunc.Equals("SIGMOID_FUNCTION"))
{
loadedNetwork.m_arOutputNodes[i].m_activeFuncType = ActionvationFunction.SIGMOID_FUNCTION;
}
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
return(null);
}
return(loadedNetwork);
}
private void btnGetData_Click(object sender, EventArgs e)
{
_dataSeries = new List <double>();
System.IO.StreamReader file = null;
string line = null;
bool isFormatFileRight = true;
int beginRow = Convert.ToInt32(this.txtTrainDataFromRow.Text);
int endRow = Convert.ToInt32(this.txtTrainDataToRow.Text);
int columnSelected = Convert.ToInt32(this.txtTrainDataColumn.Text);
int idxRow = 0;
try
{
file = new System.IO.StreamReader(m_TrainingDataFile);
while ((line = file.ReadLine()) != null)
{
idxRow++;
if (idxRow < beginRow || idxRow > endRow)
{
continue;
}
char[] delimiterChars = { ' ', ',' };
List <String> words = new List <string>();
words.AddRange(line.Split(delimiterChars));
words.RemoveAll(item => "" == item);
if (columnSelected <= words.Count)
{
_dataSeries.Add(Double.Parse(words[columnSelected - 1]));
}
else
{
isFormatFileRight = false;
break;
}
}
if (!isFormatFileRight)
{
MessageBox.Show("Input is wrong format", null, MessageBoxButtons.OK, MessageBoxIcon.Error);
_dataSeries = null;
}
}
catch (System.OutOfMemoryException outOfMemory)
{
_dataSeries = null;
MessageBox.Show("File does not found", null, MessageBoxButtons.OK, MessageBoxIcon.Error);
}
catch (System.IO.IOException io)
{
_dataSeries = null;
MessageBox.Show("File does not found", null, MessageBoxButtons.OK, MessageBoxIcon.Error);
}
catch (System.Exception excp)
{
_dataSeries = null;
MessageBox.Show("Input is wrong format", null, MessageBoxButtons.OK, MessageBoxIcon.Error);
}
finally
{
if (file != null)
{
file.Close();
}
}
if (_dataSeries != null)
{
SettingGetData();
ARIMAModel = new ARIMA();
NeuralModel = new Neural();
ARIMAModel.SetData(_dataSeries);
}
else
{
MessageBox.Show("Load data fail", null, MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}